u=lambda*a:a
b=u
x=lambda f,a,b:[int(f<=a),(b-f)/(b-a)][a<f<b]
y=lambda f,p,q,r:o(0,p)*o(f,q)+(1-o(0,p))*o(f,r)
o=lambda f,p:[x,y][len(p)-2](f,*p)
t="""over(4.356, uniform(-4.873, 2.441)) -> 0.0
over(2.226, uniform(-1.922, 2.664)) -> 0.09550806803314438
over(-4.353, uniform(-7.929, -0.823)) -> 0.49676329862088375
over(-2.491, uniform(-0.340, 6.453)) -> 1.0
over(0.738, blend(uniform(-5.233, 3.384), uniform(2.767, 8.329), uniform(-2.769, 6.497))) -> 0.7701533851999125
over(-3.577, blend(uniform(-3.159, 0.070), blend(blend(uniform(-4.996, 4.851), uniform(-7.516, 1.455), uniform(-0.931, 7.292)), blend(uniform(-5.437, -0.738), uniform(-8.272, -2.316), uniform(-3.225, 1.201)), uniform(3.097, 6.792)), uniform(-8.215, 0.817))) -> 0.4976245638164541
over(3.243, blend(blend(uniform(-4.909, 2.003), uniform(-4.158, 4.622), blend(uniform(0.572, 5.874), uniform(-0.573, 4.716), blend(uniform(-5.279, 3.702), uniform(-6.564, 1.373), uniform(-6.585, 2.802)))), uniform(-3.148, 2.015), blend(uniform(-6.235, -5.629), uniform(-4.647, -1.056), uniform(-0.384, 2.050)))) -> 0.0
over(-3.020, blend(blend(uniform(-0.080, 6.148), blend(uniform(1.691, 6.439), uniform(-7.086, 2.158), uniform(3.423, 6.773)), uniform(-1.780, 2.381)), blend(uniform(-1.754, 1.943), uniform(-0.046, 6.327), blend(uniform(-6.667, 2.543), uniform(0.656, 7.903), blend(uniform(-8.673, 3.639), uniform(-7.606, 1.435), uniform(-5.138, -2.409)))), uniform(-8.008, -0.317))) -> 0.4487803553043079"""
uniform=u
blend=b
over=o
for test in t.split('\n'):
case,res = test.split(' -> ')
print eval(case),res
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